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{
"cells": [
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import open_clip\n",
"import torch\n",
"from tqdm.notebook import tqdm\n",
"import pandas as pd\n",
"import os\n",
"\n",
"device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
"\n",
"PROMPTS = [\n",
" '{0}',\n",
" 'an image of {0}',\n",
" 'a photo of {0}',\n",
" '{0} on a photo',\n",
" 'a photo of a person named {0}',\n",
" 'a person named {0}',\n",
" 'a man named {0}',\n",
" 'a woman named {0}',\n",
" 'the name of the person is {0}',\n",
" 'a photo of a person with the name {0}',\n",
" '{0} at a gala',\n",
" 'a photo of the celebrity {0}',\n",
" 'actor {0}',\n",
" 'actress {0}',\n",
" 'a colored photo of {0}',\n",
" 'a black and white photo of {0}',\n",
" 'a cool photo of {0}',\n",
" 'a cropped photo of {0}',\n",
" 'a cropped image of {0}',\n",
" '{0} in a suit',\n",
" '{0} in a dress'\n",
"]\n",
"MODEL_NAMES = ['ViT-B-32', 'ViT-B-16', 'ViT-L-14']\n",
"SEED = 42"
]
},
{
"cell_type": "code",
"execution_count": 2,
"outputs": [],
"source": [
"# init clip\n",
"models = {}\n",
"preprocessings = {}\n",
"tokenizers = {}\n",
"for model_name in MODEL_NAMES:\n",
" model, _, preprocess = open_clip.create_model_and_transforms(model_name, pretrained='laion400m_e32')\n",
" preprocessings[model_name] = preprocess\n",
" model = model.eval()\n",
" models[model_name] = model\n",
" tokenizers[model_name] = open_clip.get_tokenizer(model_name)"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 3,
"outputs": [],
"source": [
"# define a function to get the predictions for an actor/actress\n",
"@torch.no_grad()\n",
"def get_text_embeddings(model, context, context_batchsize=1_000, use_tqdm=False):\n",
" context_batchsize = context_batchsize * torch.cuda.device_count()\n",
" # if there is not batches for the context unsqueeze it\n",
" if context.dim() < 3:\n",
" context = context.unsqueeze(0)\n",
"\n",
" # get the batch size, the number of labels and the sequence length\n",
" seq_len = context.shape[-1]\n",
" viewed_context = context.view(-1, seq_len)\n",
"\n",
" text_features = []\n",
" for context_batch_idx in tqdm(range(0, len(viewed_context), context_batchsize), desc=\"Calculating Text Embeddings\",\n",
" disable=not use_tqdm):\n",
" context_batch = viewed_context[context_batch_idx:context_batch_idx + context_batchsize]\n",
" batch_text_features = model.encode_text(context_batch, normalize=True).cpu()\n",
"\n",
" text_features.append(batch_text_features)\n",
" text_features = torch.cat(text_features).view(list(context.shape[:-1]) + [-1])\n",
"\n",
" return text_features"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 4,
"outputs": [
{
"data": {
"text/plain": " first_name sex last_name\n0 Eliana f Cardenas\n1 Meghann f Daniels\n2 Ada f Stevenson\n3 Elsa f Leblanc\n4 Avah f Lambert\n... ... .. ...\n9995 Kasen m Barker\n9996 Camryn m Roberts\n9997 Henry m Whitaker\n9998 Adin m Richards\n9999 Charley m Herman\n\n[10000 rows x 3 columns]",
"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>first_name</th>\n <th>sex</th>\n <th>last_name</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>Eliana</td>\n <td>f</td>\n <td>Cardenas</td>\n </tr>\n <tr>\n <th>1</th>\n <td>Meghann</td>\n <td>f</td>\n <td>Daniels</td>\n </tr>\n <tr>\n <th>2</th>\n <td>Ada</td>\n <td>f</td>\n <td>Stevenson</td>\n </tr>\n <tr>\n <th>3</th>\n <td>Elsa</td>\n <td>f</td>\n <td>Leblanc</td>\n </tr>\n <tr>\n <th>4</th>\n <td>Avah</td>\n <td>f</td>\n <td>Lambert</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>9995</th>\n <td>Kasen</td>\n <td>m</td>\n <td>Barker</td>\n </tr>\n <tr>\n <th>9996</th>\n <td>Camryn</td>\n <td>m</td>\n <td>Roberts</td>\n </tr>\n <tr>\n <th>9997</th>\n <td>Henry</td>\n <td>m</td>\n <td>Whitaker</td>\n </tr>\n <tr>\n <th>9998</th>\n <td>Adin</td>\n <td>m</td>\n <td>Richards</td>\n </tr>\n <tr>\n <th>9999</th>\n <td>Charley</td>\n <td>m</td>\n <td>Herman</td>\n </tr>\n </tbody>\n</table>\n<p>10000 rows × 3 columns</p>\n</div>"
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# load the possible names\n",
"possible_names = pd.read_csv('./full_names.csv', index_col=0)\n",
"possible_names\n",
"# possible_names_list = (possible_names['first_name'] + ' ' + possible_names['last_name']).tolist()\n",
"# possible_names_list[:5]"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 5,
"outputs": [
{
"data": {
"text/plain": " first_name sex last_name prompt_0 prompt_1 \\\n0 Eliana f Cardenas Eliana Cardenas an image of Eliana Cardenas \n1 Meghann f Daniels Meghann Daniels an image of Meghann Daniels \n2 Ada f Stevenson Ada Stevenson an image of Ada Stevenson \n3 Elsa f Leblanc Elsa Leblanc an image of Elsa Leblanc \n4 Avah f Lambert Avah Lambert an image of Avah Lambert \n... ... .. ... ... ... \n9995 Kasen m Barker Kasen Barker an image of Kasen Barker \n9996 Camryn m Roberts Camryn Roberts an image of Camryn Roberts \n9997 Henry m Whitaker Henry Whitaker an image of Henry Whitaker \n9998 Adin m Richards Adin Richards an image of Adin Richards \n9999 Charley m Herman Charley Herman an image of Charley Herman \n\n prompt_2 prompt_3 \\\n0 a photo of Eliana Cardenas Eliana Cardenas on a photo \n1 a photo of Meghann Daniels Meghann Daniels on a photo \n2 a photo of Ada Stevenson Ada Stevenson on a photo \n3 a photo of Elsa Leblanc Elsa Leblanc on a photo \n4 a photo of Avah Lambert Avah Lambert on a photo \n... ... ... \n9995 a photo of Kasen Barker Kasen Barker on a photo \n9996 a photo of Camryn Roberts Camryn Roberts on a photo \n9997 a photo of Henry Whitaker Henry Whitaker on a photo \n9998 a photo of Adin Richards Adin Richards on a photo \n9999 a photo of Charley Herman Charley Herman on a photo \n\n prompt_4 \\\n0 a photo of a person named Eliana Cardenas \n1 a photo of a person named Meghann Daniels \n2 a photo of a person named Ada Stevenson \n3 a photo of a person named Elsa Leblanc \n4 a photo of a person named Avah Lambert \n... ... \n9995 a photo of a person named Kasen Barker \n9996 a photo of a person named Camryn Roberts \n9997 a photo of a person named Henry Whitaker \n9998 a photo of a person named Adin Richards \n9999 a photo of a person named Charley Herman \n\n prompt_5 prompt_6 ... \\\n0 a person named Eliana Cardenas a man named Eliana Cardenas ... \n1 a person named Meghann Daniels a man named Meghann Daniels ... \n2 a person named Ada Stevenson a man named Ada Stevenson ... \n3 a person named Elsa Leblanc a man named Elsa Leblanc ... \n4 a person named Avah Lambert a man named Avah Lambert ... \n... ... ... ... \n9995 a person named Kasen Barker a man named Kasen Barker ... \n9996 a person named Camryn Roberts a man named Camryn Roberts ... \n9997 a person named Henry Whitaker a man named Henry Whitaker ... \n9998 a person named Adin Richards a man named Adin Richards ... \n9999 a person named Charley Herman a man named Charley Herman ... \n\n prompt_11 prompt_12 \\\n0 a photo of the celebrity Eliana Cardenas actor Eliana Cardenas \n1 a photo of the celebrity Meghann Daniels actor Meghann Daniels \n2 a photo of the celebrity Ada Stevenson actor Ada Stevenson \n3 a photo of the celebrity Elsa Leblanc actor Elsa Leblanc \n4 a photo of the celebrity Avah Lambert actor Avah Lambert \n... ... ... \n9995 a photo of the celebrity Kasen Barker actor Kasen Barker \n9996 a photo of the celebrity Camryn Roberts actor Camryn Roberts \n9997 a photo of the celebrity Henry Whitaker actor Henry Whitaker \n9998 a photo of the celebrity Adin Richards actor Adin Richards \n9999 a photo of the celebrity Charley Herman actor Charley Herman \n\n prompt_13 prompt_14 \\\n0 actress Eliana Cardenas a colored photo of Eliana Cardenas \n1 actress Meghann Daniels a colored photo of Meghann Daniels \n2 actress Ada Stevenson a colored photo of Ada Stevenson \n3 actress Elsa Leblanc a colored photo of Elsa Leblanc \n4 actress Avah Lambert a colored photo of Avah Lambert \n... ... ... \n9995 actress Kasen Barker a colored photo of Kasen Barker \n9996 actress Camryn Roberts a colored photo of Camryn Roberts \n9997 actress Henry Whitaker a colored photo of Henry Whitaker \n9998 actress Adin Richards a colored photo of Adin Richards \n9999 actress Charley Herman a colored photo of Charley Herman \n\n prompt_15 \\\n0 a black and white photo of Eliana Cardenas \n1 a black and white photo of Meghann Daniels \n2 a black and white photo of Ada Stevenson \n3 a black and white photo of Elsa Leblanc \n4 a black and white photo of Avah Lambert \n... ... \n9995 a black and white photo of Kasen Barker \n9996 a black and white photo of Camryn Roberts \n9997 a black and white photo of Henry Whitaker \n9998 a black and white photo of Adin Richards \n9999 a black and white photo of Charley Herman \n\n prompt_16 prompt_17 \\\n0 a cool photo of Eliana Cardenas a cropped photo of Eliana Cardenas \n1 a cool photo of Meghann Daniels a cropped photo of Meghann Daniels \n2 a cool photo of Ada Stevenson a cropped photo of Ada Stevenson \n3 a cool photo of Elsa Leblanc a cropped photo of Elsa Leblanc \n4 a cool photo of Avah Lambert a cropped photo of Avah Lambert \n... ... ... \n9995 a cool photo of Kasen Barker a cropped photo of Kasen Barker \n9996 a cool photo of Camryn Roberts a cropped photo of Camryn Roberts \n9997 a cool photo of Henry Whitaker a cropped photo of Henry Whitaker \n9998 a cool photo of Adin Richards a cropped photo of Adin Richards \n9999 a cool photo of Charley Herman a cropped photo of Charley Herman \n\n prompt_18 prompt_19 \\\n0 a cropped image of Eliana Cardenas Eliana Cardenas in a suit \n1 a cropped image of Meghann Daniels Meghann Daniels in a suit \n2 a cropped image of Ada Stevenson Ada Stevenson in a suit \n3 a cropped image of Elsa Leblanc Elsa Leblanc in a suit \n4 a cropped image of Avah Lambert Avah Lambert in a suit \n... ... ... \n9995 a cropped image of Kasen Barker Kasen Barker in a suit \n9996 a cropped image of Camryn Roberts Camryn Roberts in a suit \n9997 a cropped image of Henry Whitaker Henry Whitaker in a suit \n9998 a cropped image of Adin Richards Adin Richards in a suit \n9999 a cropped image of Charley Herman Charley Herman in a suit \n\n prompt_20 \n0 Eliana Cardenas in a dress \n1 Meghann Daniels in a dress \n2 Ada Stevenson in a dress \n3 Elsa Leblanc in a dress \n4 Avah Lambert in a dress \n... ... \n9995 Kasen Barker in a dress \n9996 Camryn Roberts in a dress \n9997 Henry Whitaker in a dress \n9998 Adin Richards in a dress \n9999 Charley Herman in a dress \n\n[10000 rows x 24 columns]",
"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>first_name</th>\n <th>sex</th>\n <th>last_name</th>\n <th>prompt_0</th>\n <th>prompt_1</th>\n <th>prompt_2</th>\n <th>prompt_3</th>\n <th>prompt_4</th>\n <th>prompt_5</th>\n <th>prompt_6</th>\n <th>...</th>\n <th>prompt_11</th>\n <th>prompt_12</th>\n <th>prompt_13</th>\n <th>prompt_14</th>\n <th>prompt_15</th>\n <th>prompt_16</th>\n <th>prompt_17</th>\n <th>prompt_18</th>\n <th>prompt_19</th>\n <th>prompt_20</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>Eliana</td>\n <td>f</td>\n <td>Cardenas</td>\n <td>Eliana Cardenas</td>\n <td>an image of Eliana Cardenas</td>\n <td>a photo of Eliana Cardenas</td>\n <td>Eliana Cardenas on a photo</td>\n <td>a photo of a person named Eliana Cardenas</td>\n <td>a person named Eliana Cardenas</td>\n <td>a man named Eliana Cardenas</td>\n <td>...</td>\n <td>a photo of the celebrity Eliana Cardenas</td>\n <td>actor Eliana Cardenas</td>\n <td>actress Eliana Cardenas</td>\n <td>a colored photo of Eliana Cardenas</td>\n <td>a black and white photo of Eliana Cardenas</td>\n <td>a cool photo of Eliana Cardenas</td>\n <td>a cropped photo of Eliana Cardenas</td>\n <td>a cropped image of Eliana Cardenas</td>\n <td>Eliana Cardenas in a suit</td>\n <td>Eliana Cardenas in a dress</td>\n </tr>\n <tr>\n <th>1</th>\n <td>Meghann</td>\n <td>f</td>\n <td>Daniels</td>\n <td>Meghann Daniels</td>\n <td>an image of Meghann Daniels</td>\n <td>a photo of Meghann Daniels</td>\n <td>Meghann Daniels on a photo</td>\n <td>a photo of a person named Meghann Daniels</td>\n <td>a person named Meghann Daniels</td>\n <td>a man named Meghann Daniels</td>\n <td>...</td>\n <td>a photo of the celebrity Meghann Daniels</td>\n <td>actor Meghann Daniels</td>\n <td>actress Meghann Daniels</td>\n <td>a colored photo of Meghann Daniels</td>\n <td>a black and white photo of Meghann Daniels</td>\n <td>a cool photo of Meghann Daniels</td>\n <td>a cropped photo of Meghann Daniels</td>\n <td>a cropped image of Meghann Daniels</td>\n <td>Meghann Daniels in a suit</td>\n <td>Meghann Daniels in a dress</td>\n </tr>\n <tr>\n <th>2</th>\n <td>Ada</td>\n <td>f</td>\n <td>Stevenson</td>\n <td>Ada Stevenson</td>\n <td>an image of Ada Stevenson</td>\n <td>a photo of Ada Stevenson</td>\n <td>Ada Stevenson on a photo</td>\n <td>a photo of a person named Ada Stevenson</td>\n <td>a person named Ada Stevenson</td>\n <td>a man named Ada Stevenson</td>\n <td>...</td>\n <td>a photo of the celebrity Ada Stevenson</td>\n <td>actor Ada Stevenson</td>\n <td>actress Ada Stevenson</td>\n <td>a colored photo of Ada Stevenson</td>\n <td>a black and white photo of Ada Stevenson</td>\n <td>a cool photo of Ada Stevenson</td>\n <td>a cropped photo of Ada Stevenson</td>\n <td>a cropped image of Ada Stevenson</td>\n <td>Ada Stevenson in a suit</td>\n <td>Ada Stevenson in a dress</td>\n </tr>\n <tr>\n <th>3</th>\n <td>Elsa</td>\n <td>f</td>\n <td>Leblanc</td>\n <td>Elsa Leblanc</td>\n <td>an image of Elsa Leblanc</td>\n <td>a photo of Elsa Leblanc</td>\n <td>Elsa Leblanc on a photo</td>\n <td>a photo of a person named Elsa Leblanc</td>\n <td>a person named Elsa Leblanc</td>\n <td>a man named Elsa Leblanc</td>\n <td>...</td>\n <td>a photo of the celebrity Elsa Leblanc</td>\n <td>actor Elsa Leblanc</td>\n <td>actress Elsa Leblanc</td>\n <td>a colored photo of Elsa Leblanc</td>\n <td>a black and white photo of Elsa Leblanc</td>\n <td>a cool photo of Elsa Leblanc</td>\n <td>a cropped photo of Elsa Leblanc</td>\n <td>a cropped image of Elsa Leblanc</td>\n <td>Elsa Leblanc in a suit</td>\n <td>Elsa Leblanc in a dress</td>\n </tr>\n <tr>\n <th>4</th>\n <td>Avah</td>\n <td>f</td>\n <td>Lambert</td>\n <td>Avah Lambert</td>\n <td>an image of Avah Lambert</td>\n <td>a photo of Avah Lambert</td>\n <td>Avah Lambert on a photo</td>\n <td>a photo of a person named Avah Lambert</td>\n <td>a person named Avah Lambert</td>\n <td>a man named Avah Lambert</td>\n <td>...</td>\n <td>a photo of the celebrity Avah Lambert</td>\n <td>actor Avah Lambert</td>\n <td>actress Avah Lambert</td>\n <td>a colored photo of Avah Lambert</td>\n <td>a black and white photo of Avah Lambert</td>\n <td>a cool photo of Avah Lambert</td>\n <td>a cropped photo of Avah Lambert</td>\n <td>a cropped image of Avah Lambert</td>\n <td>Avah Lambert in a suit</td>\n <td>Avah Lambert in a dress</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>9995</th>\n <td>Kasen</td>\n <td>m</td>\n <td>Barker</td>\n <td>Kasen Barker</td>\n <td>an image of Kasen Barker</td>\n <td>a photo of Kasen Barker</td>\n <td>Kasen Barker on a photo</td>\n <td>a photo of a person named Kasen Barker</td>\n <td>a person named Kasen Barker</td>\n <td>a man named Kasen Barker</td>\n <td>...</td>\n <td>a photo of the celebrity Kasen Barker</td>\n <td>actor Kasen Barker</td>\n <td>actress Kasen Barker</td>\n <td>a colored photo of Kasen Barker</td>\n <td>a black and white photo of Kasen Barker</td>\n <td>a cool photo of Kasen Barker</td>\n <td>a cropped photo of Kasen Barker</td>\n <td>a cropped image of Kasen Barker</td>\n <td>Kasen Barker in a suit</td>\n <td>Kasen Barker in a dress</td>\n </tr>\n <tr>\n <th>9996</th>\n <td>Camryn</td>\n <td>m</td>\n <td>Roberts</td>\n <td>Camryn Roberts</td>\n <td>an image of Camryn Roberts</td>\n <td>a photo of Camryn Roberts</td>\n <td>Camryn Roberts on a photo</td>\n <td>a photo of a person named Camryn Roberts</td>\n <td>a person named Camryn Roberts</td>\n <td>a man named Camryn Roberts</td>\n <td>...</td>\n <td>a photo of the celebrity Camryn Roberts</td>\n <td>actor Camryn Roberts</td>\n <td>actress Camryn Roberts</td>\n <td>a colored photo of Camryn Roberts</td>\n <td>a black and white photo of Camryn Roberts</td>\n <td>a cool photo of Camryn Roberts</td>\n <td>a cropped photo of Camryn Roberts</td>\n <td>a cropped image of Camryn Roberts</td>\n <td>Camryn Roberts in a suit</td>\n <td>Camryn Roberts in a dress</td>\n </tr>\n <tr>\n <th>9997</th>\n <td>Henry</td>\n <td>m</td>\n <td>Whitaker</td>\n <td>Henry Whitaker</td>\n <td>an image of Henry Whitaker</td>\n <td>a photo of Henry Whitaker</td>\n <td>Henry Whitaker on a photo</td>\n <td>a photo of a person named Henry Whitaker</td>\n <td>a person named Henry Whitaker</td>\n <td>a man named Henry Whitaker</td>\n <td>...</td>\n <td>a photo of the celebrity Henry Whitaker</td>\n <td>actor Henry Whitaker</td>\n <td>actress Henry Whitaker</td>\n <td>a colored photo of Henry Whitaker</td>\n <td>a black and white photo of Henry Whitaker</td>\n <td>a cool photo of Henry Whitaker</td>\n <td>a cropped photo of Henry Whitaker</td>\n <td>a cropped image of Henry Whitaker</td>\n <td>Henry Whitaker in a suit</td>\n <td>Henry Whitaker in a dress</td>\n </tr>\n <tr>\n <th>9998</th>\n <td>Adin</td>\n <td>m</td>\n <td>Richards</td>\n <td>Adin Richards</td>\n <td>an image of Adin Richards</td>\n <td>a photo of Adin Richards</td>\n <td>Adin Richards on a photo</td>\n <td>a photo of a person named Adin Richards</td>\n <td>a person named Adin Richards</td>\n <td>a man named Adin Richards</td>\n <td>...</td>\n <td>a photo of the celebrity Adin Richards</td>\n <td>actor Adin Richards</td>\n <td>actress Adin Richards</td>\n <td>a colored photo of Adin Richards</td>\n <td>a black and white photo of Adin Richards</td>\n <td>a cool photo of Adin Richards</td>\n <td>a cropped photo of Adin Richards</td>\n <td>a cropped image of Adin Richards</td>\n <td>Adin Richards in a suit</td>\n <td>Adin Richards in a dress</td>\n </tr>\n <tr>\n <th>9999</th>\n <td>Charley</td>\n <td>m</td>\n <td>Herman</td>\n <td>Charley Herman</td>\n <td>an image of Charley Herman</td>\n <td>a photo of Charley Herman</td>\n <td>Charley Herman on a photo</td>\n <td>a photo of a person named Charley Herman</td>\n <td>a person named Charley Herman</td>\n <td>a man named Charley Herman</td>\n <td>...</td>\n <td>a photo of the celebrity Charley Herman</td>\n <td>actor Charley Herman</td>\n <td>actress Charley Herman</td>\n <td>a colored photo of Charley Herman</td>\n <td>a black and white photo of Charley Herman</td>\n <td>a cool photo of Charley Herman</td>\n <td>a cropped photo of Charley Herman</td>\n <td>a cropped image of Charley Herman</td>\n <td>Charley Herman in a suit</td>\n <td>Charley Herman in a dress</td>\n </tr>\n </tbody>\n</table>\n<p>10000 rows × 24 columns</p>\n</div>"
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# populate the prompts with the possible names\n",
"prompts = []\n",
"for idx, row in possible_names.iterrows():\n",
" df_dict = row.to_dict()\n",
" name = f'{row[\"first_name\"]} {row[\"last_name\"]}'\n",
" for prompt_idx, prompt in enumerate(PROMPTS):\n",
" df_dict[f'prompt_{prompt_idx}'] = prompt.format(name)\n",
" prompts.append(df_dict)\n",
"prompts = pd.DataFrame(prompts)\n",
"prompts"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 7,
"outputs": [],
"source": [
"label_context_vecs = []\n",
"for i in range(len(PROMPTS)):\n",
" context = open_clip.tokenize(prompts[f'prompt_{i}'].to_numpy())\n",
" label_context_vecs.append(context)\n",
"label_context_vecs = torch.stack(label_context_vecs)"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 8,
"outputs": [
{
"data": {
"text/plain": "Calculating Text Embeddings: 0%| | 0/210 [00:00<?, ?it/s]",
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "4267d43b498f481db5cbf7e709c9ace3"
}
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": "Calculating Text Embeddings: 0%| | 0/210 [00:00<?, ?it/s]",
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"version_major": 2,
"version_minor": 0,
"model_id": "34a21714ab4d42b2beaa3024bcdd8fdd"
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"data": {
"text/plain": "Calculating Text Embeddings: 0%| | 0/210 [00:00<?, ?it/s]",
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"version_major": 2,
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"model_id": "3278ad478d7d455da8b03d954fbc4558"
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"source": [
"label_context_vecs = label_context_vecs.to(device)\n",
"\n",
"text_embeddings_per_model = {}\n",
"for model_name, model in models.items():\n",
" model = model.to(device)\n",
" text_embeddings = get_text_embeddings(model, label_context_vecs, use_tqdm=True, context_batchsize=1_000)\n",
" text_embeddings_per_model[model_name] = text_embeddings\n",
" model = model.cpu()\n",
"\n",
"label_context_vecs = label_context_vecs.cpu()"
],
"metadata": {
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},
{
"cell_type": "code",
"execution_count": 18,
"outputs": [],
"source": [
"# save the calculated embeddings to a file\n",
"if not os.path.exists('./prompt_text_embeddings'):\n",
" os.makedirs('./prompt_text_embeddings')"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 20,
"outputs": [],
"source": [
"for model_name, _ in models.items():\n",
" torch.save(\n",
" text_embeddings_per_model[model_name],\n",
" f'./prompt_text_embeddings/{model_name}_prompt_text_embeddings.pt'\n",
" )"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": null,
"outputs": [],
"source": [],
"metadata": {
"collapsed": false
}
}
],
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|